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| Paper Abstract and Keywords | ||
| Presentation | 2023-04-13 15:20 [Invited Talk] Intelligent Vehicular IoT Systems with Collaborative Edge Computing and Federated Learning Celimuge Wu (UEC)  NS2023-6 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This work discusses two approaches to enable intelligent vehicular Internet-of-Things (IoT) systems, namely, collaborative edge computing and federated learning. First, a collaborative vehicular edge computing approach is introduced to improve the data processing capability of vehicular IoT systems by designing an approach to achieve efficient task offloading between vehicles. Second, a federated learning approach is used to share the knowledge among vehicles without exchanging raw sensor data. Some approaches for empowering federated learning in vehicular environment is also discussed. Realistic computer simulations are conducted by integrating OMNeT++, a well-used network simulator, with PyTorch, a well-known machine learning framework. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Vehicular IoT / Collaborative Edge Computing / Federated Learning / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 2, NS2023-6, pp. 31-31, April 2023. | |
| Paper # | NS2023-6 | |
| Date of Issue | 2023-04-06 (NS) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NS2023-6 |
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| Conference Information | |
| Committee | NS |
| Conference Date | 2023-04-13 - 2023-04-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nihon University, Koriyama Campus + Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2023-04-NS |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Intelligent Vehicular IoT Systems with Collaborative Edge Computing and Federated Learning |
| Sub Title (in English) | |
| Keyword(1) | Vehicular IoT |
| Keyword(2) | Collaborative Edge Computing |
| Keyword(3) | Federated Learning |
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| 1st Author's Name | Celimuge Wu |
| 1st Author's Affiliation | The University of Electro-Communications (UEC) |
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| Speaker | Author-1 |
| Date Time | 2023-04-13 15:20:00 |
| Presentation Time | 45 minutes |
| Registration for | NS |
| Paper # | NS2023-6 |
| Volume (vol) | vol.123 |
| Number (no) | no.2 |
| Page | p.31 |
| #Pages | 1 |
| Date of Issue | 2023-04-06 (NS) |
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